Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Face tracking recognition technique based on video

A recognition method and video technology, applied in the field of face tracking and recognition based on offline video, can solve the problems of face loss, failure to track back, speed up detection, etc., achieve super real-time processing speed, reduce the number of comparisons, and ensure classification correctness effect

Inactive Publication Date: 2013-10-30
刘伟华
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Another object of the present invention is to propose a video-based bottom-up face tracking and recognition method, which clusters the face activity positions into a sequence of human face activity areas, and solves the problem of traditional face tracking in discrete videos. The problem that it cannot be recovered after being lost, and the processing speed of high-definition video can reach super real-time
[0006] Another object of the present invention is to adopt a down-sampling method for large-format videos, and at the same time use block-based LBP operators (Block-BLP) to extract features and train face detectors to speed up detection and overcome the existing technology. The problem that face detection and recognition cannot realize real-time processing of high-definition video
[0007] Another object of the present invention is to overcome the problems of false detection and missed detection during face detection in the prior art by adopting a preprocessing program for eliminating noise face regions and connection breakpoints.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Face tracking recognition technique based on video
  • Face tracking recognition technique based on video
  • Face tracking recognition technique based on video

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0049] The present invention will be further described in detail below in conjunction with specific embodiments.

[0050] figure 1 A specific implementation flow of the video-based face tracking and recognition method of the present invention is given. In step (2), a face detection operation is performed on the decoded video frame image. The present invention adopts the features of the local binary pattern (Block-Local Binary Pattern, BLBP) with regional weights (face images and non-face images) to be introduced into the AdaBoost face detection framework. LBP is an operator that describes the contrast relationship in the local area of ​​an image. Its calculation formula is as follows:

[0051] LBP P , R = Σ i = 0 P - 1 s (...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a face tracking recognition technique based on a video. The technique provided by the invention comprises the following steps: detecting the decoded video frame by frame; merging the number of faces and the position information of the faces into face activity position sequences; preprocessing the sequences; clustering the face activity position sequences into the face continuous activity region sequence of the same person by adopting a tracking algorithm; selecting an optimal face from each sequence by adopting face quality evaluation; carrying out normalization processing; carrying out Gabor conversion in a frequency region; carrying out histogram statistics on a converted image; solving a characteristic value; and finally, carrying out two-two subtraction on the characteristic values of the optimal faces in the different sequences and inputting the obtained statistic attribute characteristic value into a face recognizer for face matching, thereby recognizing the face activity tracking sequence of each person. Through the technique provided by the invention, the accuracy of sequence classification can be ensured, the times for characteristic extraction and face comparison are reduced, the problem that the faces cannot be tracked after being lost in the traditional face tracking is solved, and super real-time processing of a high-definition video is realized.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition, and in particular relates to a bottom-up face tracking recognition method based on offline video. Background technique [0002] As a typical biometric identification technology, face recognition technology is favored by people for its naturalness, high reliability, and high degree of automation. Wide application prospects. For example, the public security industry needs to find and lock specific people's activity areas and activity periods in massive videos, or the mosaic processing of faces in program editing in the radio and television industry requires the use of face tracking and recognition technology in offline videos. [0003] In some video media libraries, if you want to find someone's activity period, the traditional method mainly relies on manual video browsing, which can imagine the heavy workload and low work efficiency. For example, in the non-linear editing of TV progr...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
Inventor 刘伟华
Owner 刘伟华
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Eureka Blog
Learn More
PatSnap group products